Per-User Pricing Was Built on Labor. AI Just Changed the Labor.

Most MSPs already know their pricing is under strain. An Omnia poll of 255 MSPs found that only 40% are sticking with traditional per-user pricing, while 60% are reevaluating it or moving toward hybrid, outcome-based, or consumption models. Close to 43% are actively looking at alternatives to per-user pricing, and another 17% admit they need to change but have no clear direction.

That last group is the one to watch. Plenty of MSPs can feel the ground moving. Very few have a plan.

Should MSPs change their pricing model as AI lowers service delivery costs?

Yes. Change the unit you charge for, and hold your price. When AI shrinks the labor behind a contract, a pricing model built on that labor loses its footing. MSPs who wait for clients to notice will end up negotiating from behind.

The goal is simple. Keep the efficiency gain as margin. That means pricing on what the client gets, with labor hours out of the equation.

Why does per-user pricing break when AI cuts labor?

Every per-user price is an hours estimate in disguise.

MSPs built that number the same way for years. Estimate the tickets. Estimate the technician time. Add margin. The seat price was always a stand-in for labor.

Now look at where that labor goes. When we ran the numbers on what inaccurate triage actually costs, a mid-sized MSP was losing roughly $170,000 a year to rework alone.

Automation pulls that work out. Fewer touches per ticket. Faster resolution. Less dispatch overhead. Great for your MSP profitability. It also means the hours that justified your per-user number are disappearing, and your clients read the same headlines you do.

What happens if MSPs just lower their prices?

You hand your efficiency gain to the client and start a race you can’t win.

Cutting price feels fair. Delivery got cheaper, so the bill should too. Follow it out, though. A competitor cuts deeper. Your client asks why you can’t match. Your margin lands right back where it started, and now you’ve trained the market to expect a discount every time you get better.

That’s the real enemy: pricing the input. Hours, touches, headcount. Any model anchored to effort punishes you for improving.

Analysts see the same risk. As AI-driven service becomes normal, clients will assume delivery costs less and push for lower prices, unless MSPs can clearly show the value behind what they charge. And the shift is coming fast. IDC expects 30% of all service provider contracts to be outcome-based by 2029, driven by agentic AI. giantrocketshipidc

What should MSPs price on instead?

Price on outcomes clients can see. Response time. Resolution time. After-hours coverage. Uptime. Fewer repeat issues.

Clients judge you by one thing: how fast their people get back to work. Outcome pricing finally lines the bill up with that.

Most MSPs shouldn’t flip the whole model overnight. A hybrid works better:

• Keep a per-user base for core coverage.
• Add outcome-backed tiers on top. Guaranteed response times. 24/7 coverage. Faster resolution commitments.
• Start with new clients and renewals. Migrate existing contracts once you’ve proven the numbers.

This is where automation turns into something you can sell. Thread Voice AI answers after-hours calls, so 24/7 coverage becomes a premium tier instead of a staffing headache. Super Magic takes repetitive workflows off your team’s plate, so you can commit to faster resolution and scale without hiring. Every hour of work that disappears is capacity you can package and price.

How do MSPs prove the value behind an outcome-based price?

With numbers. If you sell outcomes, you have to measure them.

Before you reprice anything, know these:

• Cost per ticket. The full labor cost from open to close.
• Labor hours per resolution. Time worked, separate from time waiting in a queue.
• Response and resolution times by client. The outcomes you’ll be putting in writing.
• Margin by client. Which accounts carry the business and which quietly drain it.

If those numbers live across five tools and a spreadsheet, outcome pricing turns into guesswork. Clean data starts at intake. Automated ticket triage sets category, priority, and time entries the moment a ticket arrives, so the numbers you price on are numbers you can trust.

Where should an MSP start?

Start with your cost to serve. Then move in this order:

1. Measure your current cost per ticket and margin by client.
2. Automate dispatch and triage first. That’s where the hidden labor lives.
3. Build one outcome-backed tier and offer it to new clients.
4. Use a couple of quarters of real data to bring renewals onto the new model.

AI is going to lower the cost of delivering service. That part is settled. Who keeps the savings is still up for grabs. The MSPs pulling ahead will price on the result and keep what they save.

Find out what automation does to your cost per ticket before your clients ask. Book a Thread demo.